A systematic review of the effects of e-cigarette use on lung function
Bibliographic record
Abstract
Abstract Given the increasing use of e-cigarettes and uncertainty surrounding their safety, we conducted a systematic review to determine the effects of e-cigarettes on measures of lung function. We systematically searched EMBASE, MEDLINE, and PsycINFO databases via Ovid, the Cochrane CENTRAL database, and the Web of Science Core from 2004 until July 2021, identifying 8856 potentially eligible studies. A total of eight studies (seven studying immediate effects and one long-term effects, 273 total participants) were included. The risk of bias was assessed using the Risk of Bias in Non-randomized Studies—of Interventions (ROBINS-I) and Cochrane risk of bias tools. These studies suggest that vaping increases airway resistance but does not appear to impact forced expiratory volume in one second (FEV1), forced vital capacity (FVC), or FEV1/FVC ratio. However, given the limited size and follow-up duration of these studies, larger, long-term studies are required to further determine the effects of e-cigarettes on lung function.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".